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Driving forces of China's multisector CO2 emissions: a Log-Mean Divisia Index decomposition

机译:中国多元化器二氧化碳排放的驱动力:一种逻辑意味着Divisia指数分解

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To figure out which factor contributes more on carbon emissions caused by energy consumption, this research took multisector analysis based on the Log-Mean Divisia Index Method (LMDI) and decoupling theory to assess the driving factors of carbon dioxide (CO2) emissions in China's six sectors from 2003 to 2016. Our empirical results reveal that China's economy can be divided as three decoupling stages and exhibited a distinct tendency toward strong decoupling with a turning point in 2008. Thus, we discuss the impact of 2008 economic crisis on carbon emissions based on decomposition results. The empirical results of our study show the following five conclusions. (1) Most sectors in China are in weak decoupling state due to the inhibition of energy intensity on carbon emissions. (2) Different factors contribute differently to reducing emissions in different sectors, economic output has the most prominent effect, followed by energy intensity and population scale. (3) China's current carbon emission reduction measures benefit more on energy efficiency. (4) The economic crisis has greatly reduced energy efficiency and has no significant impact on other factors. (5) If all industries adjust their energy mix, carbon emissions in China can be reduced by almost 17% every year.
机译:为了弄清楚哪些因素有助于更加引起的能源消费碳排放量,这个研究的人在中国六大基础上,对数平均Divisia指数法(LMDI)多部门分析和去耦理论评估二氧化碳(CO2)的驱动因素排放从2003年行业至2016年我们的实证研究结果表明,中国经济在2008年因此被分为三个解耦阶段,并表现出强烈的向脱钩明显的趋势与拐点,我们讨论2008年经济危机的基础上对碳排放的影响分解结果。我们研究的实证结果表明以下五个结论。 (1)在中国大多数行业处于弱脱钩状态由于能量强度的碳排放的抑制。 (2)不同的因素不同,以减少排放不同部门贡献,经济输出具有最显着的作用,随后的能量强度和人口规模。 (3)中国目前的碳减排措施惠及更多的能源效率。 (4)经济危机大大降低了能源效率和对其他因素没有显著影响。 (5)如果所有的行业调整能源结构,可以通过每年近17%,可减少在中国的碳排放量。

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